Abstract: Embodiments relate to an adaptive glycemia monitoring and forecasting system that includes an event monitor configured to receive blood glucose levels of an individual or information about an activity performed by the individual, and generate an event output. The system includes a control module configured to pull observation data, predictor variables, and population estimated vector of covariate weightings coefficients from a database, and generate updated estimated vector of covariate weightings coefficients for the individual user based on the event output. The updated estimated vector of covariate weightings coefficients are determined by a cross-entropy loss objective function. The updated estimated vector of covariate weightings coefficients are used to predict at least one or more of a predicted hypoglycemia state, a predicted normal glycemia state, or a predicted hyperglycemia state for the individual user.